Results 131 to 140 of about 1,120 (201)

Weakly Convex Ridge Regularization for 3D Non‐Cartesian MRI Reconstruction

open access: yesMagnetic Resonance in Medicine, EarlyView.
ABSTRACT Purpose While highly accelerated non‐Cartesian acquisition protocols significantly reduce scan time, they often entail long reconstruction delays for 3D data. Deep learning–based reconstruction methods can alleviate this, but typically rely on complex, highly parametrized architectures.
German Shâma Wache   +3 more
wiley   +1 more source

Dynamic Performance Enhancement of a High‐Agility Hypersonic Mechanical System via a Learning‐Augmented Robust Control Architecture

open access: yesInternational Journal of Mechanical System Dynamics, EarlyView.
ABSTRACT The design of control systems for high‐agility mechanical systems operating in extreme environments is a significant challenge in nonlinear dynamics. This paper addresses the complex dynamic control problem of a hypersonic interceptor, modeled as a multi‐input multi‐output (MIMO) mechanical system characterized by strong aerodynamic cross ...
Mohammad Mahdi Soori   +1 more
wiley   +1 more source

The 2‐D Orthogonal Packing Problem With Multiple Levels of Prioritization: A Spatial Optimization Perspective

open access: yesNaval Research Logistics (NRL), EarlyView.
ABSTRACT This paper addresses two‐dimensional orthogonal packing within a confined space, integrating bin packing principles with facility layout concepts to address scenarios in which items must not only fit but also be arranged according to spatial priorities.
William K. Kirschenman   +4 more
wiley   +1 more source

Allocation of Indivisible Items With a Common Preference Graph: Minimizing Total Dissatisfaction

open access: yesNetworks, EarlyView.
ABSTRACT Allocating indivisible items among a set of agents is a frequently studied discrete optimization problem. In the setting considered in this work, the agents' preferences over the items are assumed to be identical. We consider a very recent measure for the overall quality of an allocation which does not rely on numerical valuations of the items.
Nina Chiarelli   +6 more
wiley   +1 more source

Safeguarded Reinforcement Learning for Dynamic Environments

open access: yesOptimal Control Applications and Methods, EarlyView.
This paper uses a combination of Reinforcement Learning and Funnel Control to train a fast and safe controller for systems operating in changing environments. Furthermore, the presented formulation overcomes former limitations associated with the need for predefined reference trajectories.
Simon Gottschalk
wiley   +1 more source

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